A 9-parameter calibrated Laplace mixture that models coarse-assignment failures as a heavy tail improves downstream geometric estimation when used as soft weights in a posterior refit.
Matching with PROSAC - pro- gressive sample consensus
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Semi-Dense Matching Uncertainty Is Not Just Local Confidence
A 9-parameter calibrated Laplace mixture that models coarse-assignment failures as a heavy tail improves downstream geometric estimation when used as soft weights in a posterior refit.